ArticleActa pharmaceutica Sinica. B2022
Prediction of lipid nanoparticles for mRNA vaccines by the machine learning algorithm.
Article in Acta pharmaceutica Sinica. B, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers.
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Who cites it
63 citing papers in PubMed, 136 citations in OpenAlex.
- From RNA design to delivery: Computational strategies for functional RNA therapeutics.Bioactive materials · 2027Review
- Nanocarrier-Based Gene Delivery Systems: Mechanisms, Clinical Translation, and Future Perspectives.Biotechnology and bioengineering · 2026Review
- Structural evolution of ionizable lipids for nucleic acid delivery.Nature reviews. Chemistry · 2026Review
- Combined HER2-targeted mRNA-LNP vaccine and radiotherapy suppress Lewis lung carcinoma growth in mice: Efficacy and mechanistic insights.Bioengineering & translational medicine · 2026Article
- Critical chemistry manufacturing and controls considerations for mRNA lipid nanoparticle translation.Discover nano · 2026Review
- A novel machine learning framework-based rapid screening of ionizable lipids in LNPs for highly-efficient mRNA expression.Acta pharmaceutica Sinica. B · 2026Article
- From serendipity to rational design: Accelerating ionizable lipid discovery with LipidAI.Acta pharmaceutica Sinica. B · 2026Article
- Post-loading ribonucleic acid into lipid nanoparticle carriers.bioRxiv : the preprint server for biology · 2026Article
- Artificial Intelligence-Driven Nanomedicine: From Drug Formulation and Nanocarrier Design to Clinical Translation.Pharmaceutics · 2026Review
- Nanoengineering Systems for Gene Therapy: Mechanisms, Modalities, and Future Directions.International journal of molecular sciences · 2026Review
- Machine learning reshapes the paradigm of nanomedicine research.Acta pharmaceutica Sinica. B · 2026Review
- Artificial intelligence in biologic drug discovery: A review of methodological evolution and therapeutic applications.Acta pharmaceutica Sinica. B · 2026Review
- Transformer-based multidimensional feature fusion for accurate prediction of lipid nanoparticles transfection efficiency.Briefings in bioinformatics · 2026Article
- Machine learning empowered formulation design, optimization and characterization of nanoparticulate drug delivery systems: Current applications, challenges, and future perspectives.Acta pharmaceutica Sinica. B · 2026Review
- Artificial intelligence-guided design of lipid nanoparticles for mRNA delivery.Acta pharmaceutica Sinica. B · 2026Review
- Applications of AI/ML in accelerating the development of pulmonary drug delivery system.Acta pharmaceutica Sinica. B · 2026Review
- Accelerate the Highly Efficient Development of mRNA Vaccines Through Advanced Computational Methods.MedComm · 2026Review
- Breaking barriers in prostate cancer: the mRNA vaccine breakthrough and what comes next.NPJ vaccines · 2026Review
- Machine Learning Prediction of Protein Adsorption on Drug-delivering Nanoparticles: A Literature Survey and Need for Future Development.Pharmaceutical research · 2026Review
- mRNA therapeutics: Transforming medicine through innovation in design, delivery, and disease treatment.Molecular therapy. Nucleic acids · 2025Review
3 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lipid nanoparticle (LNP) is commonly used to deliver mRNA vaccines. Currently, LNP optimization primarily relies on screening ionizable lipids by traditional experiments which consumes intensive cost and time. Current study attempts to apply computational methods to accelerate the LNP development for mRNA vaccines. Firstly, 325 data samples of mRNA vaccine LNP formulations with IgG titer were collected. The machine learning algorithm, lightGBM, was used to build a prediction model with good performance (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.